1. Statement of the Technical Field
The invention concerns image processing, and more particularly, an image processing method for images having different spatial and spectral resolutions.
2. Description of the Related Art
In the field of remote image sensing, two common types of images include panchromatic imagery and multi-spectral imagery. Panchromatic imagery is imagery that is obtained by a remote sensing device with a sensor designed to detect electromagnetic energy in only one very broad band. This one very broad band typically includes most of the wavelengths of visible light. Panchromatic imagery has the advantage of offering very high spatial resolution. In contrast, multi-spectral imagery is typically created from several narrow spectral bands within the visible light region and the near infrared region. Consequently, a multi-spectral image is generally comprised of two or more image data sets, each created by sensors responsive to different portions of the optical spectrum (e.g., blue, green, red, infrared). Multi-spectral images are advantageous because they contain spectral information which is not available from a similar panchromatic image. However, multi-spectral images typically have a lower spatial resolution as compared to panchromatic images.
It is often desirable to enhance a multi-spectral image with the high resolution of a panchromatic image and vice versa. Typically this process is referred to as “fusion” of the image pair. In general, there are several requirements for successfully accomplishing the fusion process. One requirement is to ensure that the radiance values of the fused image remain consistent with both the original multi-spectral image and the original panchromatic image. Typically, this requires some means of obtaining an estimate of the weights that should be applied to radiance values for pixels associated with each band of wavelengths in the fused image. If these weights are known, then it is possible to make an accurate comparison of the radiance values of pixels in the multi-spectral image to the pixels in the original panchromatic image.
Unfortunately, conventional algorithms utilized for performing the image fusion process suffer from several limitations. For example, spectral weights are typically based solely on known sensor characteristics. That is, spectral weights are typically fixed for a given sensor, modulated only by variations in spectral calibration. However, even when the spectral weights are not based solely on sensor characteristics, the obtained spectral weights are still essentially fixed for the given sensor. For example, even though spectral weights can be estimated for a particular sensor and some general imaging conditions, this estimation is typically based on a limited number of pre-selected image pairs.